Self-organized development of behaviors in spatio-temporal dynamical systems


Nonlinear distributed modeling is applied to generate conditions for the emergence of intentional behaviors afforded by the environment. The models are based on a nondeterministic dynamical approach to self-organized formation of categories using chaotic principles. Continuous and discrete models of the spatio-temporal dynamics are shown to exhibit phase transitions manifested in the form of intermittent spatio-temporal structures, which are studied in simulated environments.

Publication Title

Proceedings of the International Joint Conference on Neural Networks

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